Abstract Denial of Service and Distributed Denial of Service (DoS/DDoS) attacks have been
one of the biggest threats against communication networks and applications throughout the …

Machine Learning's widespread application owes to its ability to develop accurate and
scalable models. In cyber-security, where labeled data is scarce, Semi-Supervised Learning …

Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and
causes great harm to the network. In modern years, Botnets became one of the threads that …

To detect remote terminal (RT) spoofing attacks on MIL-STD-1553B data bus and prevent
the network paralysis of integrated avionics system (IAS) caused by misjudgment, an …

Passenger-flow anomaly detection and prediction are essential tasks for intelligent
operation of the metro system. Accurate passenger-flow representation is the foundation of …

Nowadays, botnet-based attacks are the most preva-lent cyber-threats type. It is therefore
essential to detect this kind of malware using efficient bots detection techniques. This paper …

More and more organizations are under cyberattacks. To prevent this kind of threats, it is
essential to detect them upstream by highlighting abnormal activities within networks. This …

Various machine learning or clustering techniques are applicable for identifying anomalous
activities or particular events in networks by analysing data flows. In this paper we present …

Ensuring a secure network environment is crucial, especially with the increasing number of
threats and attacks on digital systems. Implementing effective security measures, such as …

During the past decade, one of the most serious cyber threats has been the growth of botnet.
Since botnet attacks combine the characteristics of many malicious attacks, they have …